Improving Second-Generation Surveillance
Bibliographic record
Abstract
BACKGROUND: Second-generation surveillance for HIV includes measures of high-risk behaviors among the general adult population and sex workers (SW). Questionnaires are prone to social desirability biases because individuals minimize the frequency of behaviors not expected from them. OBJECTIVE: Determine whether the prostate-specific antigen (PSA) could be used as a biological marker of unprotected intercourse. METHODS: We measured the presence of PSA in vaginal secretions of women who were (n = 508) or were not (n = 658) SW presenting with vaginal discharge in health facilities of Ghana, Togo, Guinea, and Mali. The cutoff for a positive assay was determined as > or =0.4 microg/L based on a subsample of 95 non-SW claiming abstinence for 3 months. RESULTS: A positive PSA assay was correlated with infections with Neisseria gonorrhoeae, Chlamydia trachomatis, and Mycoplasma genitalium. Among non-SW, a positive PSA was more common among those with HIV, but less frequent in those better educated. Among SW and non-SW, women from Ghana were less likely to have a positive PSA and had a lower prevalence of sexually transmitted infections than those from elsewhere. CONCLUSIONS: PSA can be used as a biological marker of unprotected intercourse, allowing interventions to target efforts on those at highest risk.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.020 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.003 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".